Senior Engineering Manager, Data & Cloud Platform

Mitratech is a team of innovators focused on building world-class products for the Legal, Risk, Compliance, and HR functions. The Senior Engineering Manager, Data & Cloud Platform will lead the Data & Cloud Platform function for the AI organization, responsible for building and operating the data and infrastructure foundation that supports higher-level AI capabilities and product experiences.

Responsibilities:

• Own the cloud and data foundation for the AI organization — shared runtime infrastructure, CI/CD patterns, and platform services used by AI teams
• Design and build a unified data access layer for agents and AI features so they can interact with a coherent interface rather than bespoke storage and retrieval systems in each product
• Define where shared AI data should live — agent memory, context stores, and shared service datasets — while partnering with product teams that have compliance or customer-specific reasons to retain specialized storage patterns
• Build and operate data ingestion and transformation pipelines that support AI workloads and analytics, including ETL and lakehouse-style patterns where needed
• Shape the technical execution of the organization’s data strategy, especially around scale, operability, cost, and long-term maintainability
• Partner with the AI Quality & Governance team to support privacy-sensitive data handling, PII-aware workflows, and safe access patterns for observability, memory, and trace data
• Provide platform patterns, reference architectures, and reusable services that help product teams migrate toward shared foundations instead of building fragmented point solutions
• Hire, mentor, and grow the team over time — the function may later mature into separate data-platform and cloud-platform groups

Requirements:

• 8+ years of software engineering experience including meaningful experience leading engineers as a manager or technical lead
• Built and operated shared platform and data systems in production across multiple teams
• Strong experience with cloud infrastructure, distributed systems, developer platforms, or internal platform engineering
• Hands-on experience building or operating shared data systems: ETL/ELT pipelines, internal data services, warehouse or lakehouse environments, or other multi-team data platforms
• Experience designing platform APIs or integration layers that make complex infrastructure or fragmented systems easier for other teams to consume
• Demonstrated exposure to production AI systems, especially where data architecture and infrastructure materially affect quality, reliability, latency, or cost
• Comfort operating in ambiguous environments where the architecture is evolving and the right answer may be a combination of shared services, integration layers, and selective platform consolidation
• A strong bias toward hands-on execution, systems thinking, and building scalable foundations that other teams can trust
• Experience with agent memory, retrieval systems, semantic search, or data architectures optimized for LLM-powered applications
• Experience in multi-cloud or hybrid-cloud environments
• Experience in legal technology, enterprise SaaS, or regulated environments where access controls, auditability, and customer-specific constraints shape technical design